The paper addresses the problem of object perception for intelligent vehicle applications with main tasks of detection, tracking and classification of obstacles where multiple sensors (i.e.: lidar, camera and radar) are used. New algorithms for raw sensor data processing and sensor data fusion are introduced making the most information from all sensors in order to provide a more reliable and accurate information about objects in the vehicle environment. The proposed object perception module is implemented and tested on a demonstrator car in real-life traffics and evaluation results are presented.


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    Title :

    Object perception for intelligent vehicle applications: A multi-sensor fusion approach


    Contributors:


    Publication date :

    2014-06-01


    Size :

    2320868 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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